resurrect deleted spcg files
Yong-Dian Jian
parent
6fe2b77a25
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be0346ab87
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///* ----------------------------------------------------------------------------
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//
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// * GTSAM Copyright 2010, Georgia Tech Research Corporation,
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// * Atlanta, Georgia 30332-0415
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// * All Rights Reserved
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// * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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//
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// * See LICENSE for the license information
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//
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// * -------------------------------------------------------------------------- */
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//
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///**
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// * @file SubgraphPreconditioner.cpp
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// * @date Dec 31, 2009
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// * @author: Frank Dellaert
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// */
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//
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//#include <boost/foreach.hpp>
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//#include <gtsam/linear/SubgraphPreconditioner.h>
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//#include <gtsam/linear/JacobianFactor.h>
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//#include <gtsam/linear/GaussianFactorGraph.h>
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//
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//using namespace std;
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//
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//namespace gtsam {
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//
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// /* ************************************************************************* */
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// SubgraphPreconditioner::SubgraphPreconditioner(const sharedFG& Ab1, const sharedFG& Ab2,
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// const sharedBayesNet& Rc1, const sharedValues& xbar) :
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// Ab1_(Ab1), Ab2_(Ab2), Rc1_(Rc1), xbar_(xbar), b2bar_(gaussianErrors_(*Ab2_,*xbar)) {
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// }
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//
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// /* ************************************************************************* */
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// // x = xbar + inv(R1)*y
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// VectorValues SubgraphPreconditioner::x(const VectorValues& y) const {
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//#ifdef VECTORBTREE
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// if (!y.cloned(*xbar_)) throw
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// invalid_argument("SubgraphPreconditioner::x: y needs to be cloned from xbar");
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//#endif
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// VectorValues x = y;
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// backSubstituteInPlace(*Rc1_,x);
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// x += *xbar_;
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// return x;
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// }
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//
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//// SubgraphPreconditioner SubgraphPreconditioner::add_priors(double sigma) const {
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//// SubgraphPreconditioner result = *this ;
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//// result.Ab2_ = sharedFG(new GaussianFactorGraph(Ab2_->add_priors(sigma))) ;
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//// return result ;
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//// }
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//
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// /* ************************************************************************* */
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// double error(const SubgraphPreconditioner& sp, const VectorValues& y) {
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//
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// Errors e(y);
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// VectorValues x = sp.x(y);
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// Errors e2 = gaussianErrors(*sp.Ab2(),x);
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// return 0.5 * (dot(e, e) + dot(e2,e2));
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// }
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//
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// /* ************************************************************************* */
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// // gradient is y + inv(R1')*A2'*(A2*inv(R1)*y-b2bar),
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// VectorValues gradient(const SubgraphPreconditioner& sp, const VectorValues& y) {
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// VectorValues x = sp.x(y); // x = inv(R1)*y
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// Errors e2 = gaussianErrors(*sp.Ab2(),x);
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// VectorValues gx2 = VectorValues::Zero(y);
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// gtsam::transposeMultiplyAdd(*sp.Ab2(),1.0,e2,gx2); // A2'*e2;
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// VectorValues gy2 = gtsam::backSubstituteTranspose(*sp.Rc1(), gx2); // inv(R1')*gx2
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// return y + gy2;
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// }
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//
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// /* ************************************************************************* */
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// // Apply operator A, A*y = [I;A2*inv(R1)]*y = [y; A2*inv(R1)*y]
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// Errors operator*(const SubgraphPreconditioner& sp, const VectorValues& y) {
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//
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// Errors e(y);
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//
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// // Add A2 contribution
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// VectorValues x = y; // TODO avoid ?
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// gtsam::backSubstituteInPlace(*sp.Rc1(), x); // x=inv(R1)*y
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// Errors e2 = *sp.Ab2() * x; // A2*x
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// e.splice(e.end(), e2);
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//
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// return e;
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// }
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//
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// /* ************************************************************************* */
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// // In-place version that overwrites e
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// void multiplyInPlace(const SubgraphPreconditioner& sp, const VectorValues& y, Errors& e) {
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//
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//
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// Errors::iterator ei = e.begin();
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// for ( Index i = 0 ; i < y.size() ; ++i, ++ei ) {
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// *ei = y[i];
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// }
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//
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// // Add A2 contribution
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// VectorValues x = y; // TODO avoid ?
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// gtsam::backSubstituteInPlace(*sp.Rc1(), x); // x=inv(R1)*y
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// gtsam::multiplyInPlace(*sp.Ab2(),x,ei); // use iterator version
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// }
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//
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// /* ************************************************************************* */
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// // Apply operator A', A'*e = [I inv(R1')*A2']*e = e1 + inv(R1')*A2'*e2
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// VectorValues operator^(const SubgraphPreconditioner& sp, const Errors& e) {
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//
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// Errors::const_iterator it = e.begin();
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// VectorValues y = sp.zero();
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// for ( Index i = 0 ; i < y.size() ; ++i, ++it )
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// y[i] = *it ;
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// sp.transposeMultiplyAdd2(1.0,it,e.end(),y);
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// return y;
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// }
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//
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// /* ************************************************************************* */
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// // y += alpha*A'*e
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// void transposeMultiplyAdd
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// (const SubgraphPreconditioner& sp, double alpha, const Errors& e, VectorValues& y) {
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//
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//
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// Errors::const_iterator it = e.begin();
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// for ( Index i = 0 ; i < y.size() ; ++i, ++it ) {
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// const Vector& ei = *it;
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// axpy(alpha,ei,y[i]);
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// }
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// sp.transposeMultiplyAdd2(alpha,it,e.end(),y);
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// }
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//
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// /* ************************************************************************* */
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// // y += alpha*inv(R1')*A2'*e2
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// void SubgraphPreconditioner::transposeMultiplyAdd2 (double alpha,
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// Errors::const_iterator it, Errors::const_iterator end, VectorValues& y) const {
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//
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// // create e2 with what's left of e
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// // TODO can we avoid creating e2 by passing iterator to transposeMultiplyAdd ?
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// Errors e2;
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// while (it != end)
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// e2.push_back(*(it++));
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//
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// VectorValues x = VectorValues::Zero(y); // x = 0
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// gtsam::transposeMultiplyAdd(*Ab2_,1.0,e2,x); // x += A2'*e2
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// axpy(alpha, gtsam::backSubstituteTranspose(*Rc1_, x), y); // y += alpha*inv(R1')*x
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// }
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//
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// /* ************************************************************************* */
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// void SubgraphPreconditioner::print(const std::string& s) const {
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// cout << s << endl;
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// Ab2_->print();
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// }
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//} // nsamespace gtsam
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///* ----------------------------------------------------------------------------
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//
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// * GTSAM Copyright 2010, Georgia Tech Research Corporation,
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// * Atlanta, Georgia 30332-0415
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// * All Rights Reserved
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// * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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//
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// * See LICENSE for the license information
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//
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// * -------------------------------------------------------------------------- */
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//
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///**
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// * @file SubgraphPreconditioner.h
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// * @date Dec 31, 2009
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// * @author Frank Dellaert
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// */
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//
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//#pragma once
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//
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//#include <gtsam/linear/JacobianFactor.h>
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//#include <gtsam/linear/GaussianBayesNet.h>
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//#include <gtsam/nonlinear/Ordering.h> // FIXME shouldn't have nonlinear things in linear
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//
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//namespace gtsam {
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//
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// /**
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// * Subgraph conditioner class, as explained in the RSS 2010 submission.
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// * Starting with a graph A*x=b, we split it in two systems A1*x=b1 and A2*x=b2
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// * We solve R1*x=c1, and make the substitution y=R1*x-c1.
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// * To use the class, give the Bayes Net R1*x=c1 and Graph A2*x=b2.
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// * Then solve for yhat using CG, and solve for xhat = system.x(yhat).
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// */
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// class SubgraphPreconditioner {
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//
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// public:
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// typedef boost::shared_ptr<const GaussianBayesNet> sharedBayesNet;
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// typedef boost::shared_ptr<const FactorGraph<JacobianFactor> > sharedFG;
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// typedef boost::shared_ptr<const VectorValues> sharedValues;
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// typedef boost::shared_ptr<const Errors> sharedErrors;
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//
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// private:
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// sharedFG Ab1_, Ab2_;
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// sharedBayesNet Rc1_;
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// sharedValues xbar_;
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// sharedErrors b2bar_; /** b2 - A2*xbar */
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//
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// public:
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//
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// SubgraphPreconditioner();
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// /**
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// * Constructor
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// * @param Ab1: the Graph A1*x=b1
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// * @param Ab2: the Graph A2*x=b2
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// * @param Rc1: the Bayes Net R1*x=c1
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// * @param xbar: the solution to R1*x=c1
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// */
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// SubgraphPreconditioner(const sharedFG& Ab1, const sharedFG& Ab2, const sharedBayesNet& Rc1, const sharedValues& xbar);
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//
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// /** Access Ab1 */
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// const sharedFG& Ab1() const { return Ab1_; }
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//
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// /** Access Ab2 */
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// const sharedFG& Ab2() const { return Ab2_; }
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//
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// /** Access Rc1 */
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// const sharedBayesNet& Rc1() const { return Rc1_; }
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//
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// /**
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// * Add zero-mean i.i.d. Gaussian prior terms to each variable
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// * @param sigma Standard deviation of Gaussian
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// */
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//// SubgraphPreconditioner add_priors(double sigma) const;
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//
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// /* x = xbar + inv(R1)*y */
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// VectorValues x(const VectorValues& y) const;
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//
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// /* A zero VectorValues with the structure of xbar */
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// VectorValues zero() const {
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// VectorValues V(VectorValues::Zero(*xbar_)) ;
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// return V ;
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// }
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//
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// /**
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// * Add constraint part of the error only, used in both calls above
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// * y += alpha*inv(R1')*A2'*e2
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// * Takes a range indicating e2 !!!!
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// */
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// void transposeMultiplyAdd2(double alpha, Errors::const_iterator begin,
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// Errors::const_iterator end, VectorValues& y) const;
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//
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// /** print the object */
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// void print(const std::string& s = "SubgraphPreconditioner") const;
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// };
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//
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// /* error, given y */
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// double error(const SubgraphPreconditioner& sp, const VectorValues& y);
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//
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// /** gradient = y + inv(R1')*A2'*(A2*inv(R1)*y-b2bar) */
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// VectorValues gradient(const SubgraphPreconditioner& sp, const VectorValues& y);
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//
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// /** Apply operator A */
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// Errors operator*(const SubgraphPreconditioner& sp, const VectorValues& y);
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//
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// /** Apply operator A in place: needs e allocated already */
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// void multiplyInPlace(const SubgraphPreconditioner& sp, const VectorValues& y, Errors& e);
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//
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// /** Apply operator A' */
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// VectorValues operator^(const SubgraphPreconditioner& sp, const Errors& e);
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//
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// /**
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// * Add A'*e to y
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// * y += alpha*A'*[e1;e2] = [alpha*e1; alpha*inv(R1')*A2'*e2]
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// */
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// void transposeMultiplyAdd(const SubgraphPreconditioner& sp, double alpha, const Errors& e, VectorValues& y);
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//
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//} // namespace gtsam
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/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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#pragma once
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#include <boost/foreach.hpp>
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#include <gtsam/linear/iterative-inl.h>
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#include <gtsam/inference/graph-inl.h>
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#include <gtsam/inference/EliminationTree.h>
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using namespace std;
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namespace gtsam {
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template<class GRAPH, class LINEAR, class KEY>
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void SubgraphSolver<GRAPH,LINEAR,KEY>::replaceFactors(const typename LINEAR::shared_ptr &graph) {
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GaussianFactorGraph::shared_ptr Ab1 = boost::make_shared<GaussianFactorGraph>();
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GaussianFactorGraph::shared_ptr Ab2 = boost::make_shared<GaussianFactorGraph>();
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if (parameters_->verbosity()) cout << "split the graph ...";
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split(pairs_, *graph, *Ab1, *Ab2) ;
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if (parameters_->verbosity()) cout << ",with " << Ab1->size() << " and " << Ab2->size() << " factors" << endl;
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// // Add a HardConstraint to the root, otherwise the root will be singular
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// Key root = keys.back();
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// T_.addHardConstraint(root, theta0[root]);
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//
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// // compose the approximate solution
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// theta_bar_ = composePoses<GRAPH, Constraint, Pose, Values> (T_, tree, theta0[root]);
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LINEAR sacrificialAb1 = *Ab1; // duplicate !!!!!
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SubgraphPreconditioner::sharedBayesNet Rc1 =
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EliminationTree<GaussianFactor>::Create(sacrificialAb1)->eliminate(&EliminateQR);
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SubgraphPreconditioner::sharedValues xbar = gtsam::optimize_(*Rc1);
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pc_ = boost::make_shared<SubgraphPreconditioner>(
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Ab1->dynamicCastFactors<FactorGraph<JacobianFactor> >(), Ab2->dynamicCastFactors<FactorGraph<JacobianFactor> >(),Rc1,xbar);
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}
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template<class GRAPH, class LINEAR, class KEY>
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VectorValues::shared_ptr SubgraphSolver<GRAPH,LINEAR,KEY>::optimize() const {
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// preconditioned conjugate gradient
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VectorValues zeros = pc_->zero();
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VectorValues ybar = conjugateGradients<SubgraphPreconditioner, VectorValues, Errors>
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(*pc_, zeros, *parameters_);
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boost::shared_ptr<VectorValues> xbar = boost::make_shared<VectorValues>() ;
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*xbar = pc_->x(ybar);
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return xbar;
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}
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template<class GRAPH, class LINEAR, class KEY>
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void SubgraphSolver<GRAPH,LINEAR,KEY>::initialize(const GRAPH& G, const Values& theta0) {
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// generate spanning tree
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PredecessorMap<KEY> tree_ = gtsam::findMinimumSpanningTree<GRAPH, KEY, Constraint>(G);
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// make the ordering
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list<KEY> keys = predecessorMap2Keys(tree_);
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ordering_ = boost::make_shared<Ordering>(list<Key>(keys.begin(), keys.end()));
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// build factor pairs
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pairs_.clear();
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typedef pair<KEY,KEY> EG ;
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BOOST_FOREACH( const EG &eg, tree_ ) {
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Key key1 = Key(eg.first),
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key2 = Key(eg.second) ;
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pairs_.insert(pair<Index, Index>((*ordering_)[key1], (*ordering_)[key2])) ;
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}
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}
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} // \namespace gtsam
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@ -0,0 +1,50 @@
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///* ----------------------------------------------------------------------------
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//
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|
// * GTSAM Copyright 2010, Georgia Tech Research Corporation,
|
||||||
|
// * Atlanta, Georgia 30332-0415
|
||||||
|
// * All Rights Reserved
|
||||||
|
// * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
|
||||||
|
//
|
||||||
|
// * See LICENSE for the license information
|
||||||
|
//
|
||||||
|
// * -------------------------------------------------------------------------- */
|
||||||
|
//
|
||||||
|
//#include <gtsam/linear/SubgraphSolver.h>
|
||||||
|
//
|
||||||
|
//using namespace std;
|
||||||
|
//
|
||||||
|
//namespace gtsam {
|
||||||
|
//
|
||||||
|
///* split the gaussian factor graph Ab into Ab1 and Ab2 according to the map */
|
||||||
|
//bool split(const std::map<Index, Index> &M,
|
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|
// const GaussianFactorGraph &Ab,
|
||||||
|
// GaussianFactorGraph &Ab1,
|
||||||
|
// GaussianFactorGraph &Ab2) {
|
||||||
|
//
|
||||||
|
// Ab1 = GaussianFactorGraph();
|
||||||
|
// Ab2 = GaussianFactorGraph();
|
||||||
|
//
|
||||||
|
// for ( size_t i = 0 ; i < Ab.size() ; ++i ) {
|
||||||
|
//
|
||||||
|
// boost::shared_ptr<GaussianFactor> factor = Ab[i] ;
|
||||||
|
//
|
||||||
|
// if (factor->keys().size() > 2)
|
||||||
|
// throw(invalid_argument("split: only support factors with at most two keys"));
|
||||||
|
// if (factor->keys().size() == 1) {
|
||||||
|
// Ab1.push_back(factor);
|
||||||
|
// Ab2.push_back(factor);
|
||||||
|
// continue;
|
||||||
|
// }
|
||||||
|
// Index key1 = factor->keys()[0];
|
||||||
|
// Index key2 = factor->keys()[1];
|
||||||
|
//
|
||||||
|
// if ((M.find(key1) != M.end() && M.find(key1)->second == key2) ||
|
||||||
|
// (M.find(key2) != M.end() && M.find(key2)->second == key1))
|
||||||
|
// Ab1.push_back(factor);
|
||||||
|
// else
|
||||||
|
// Ab2.push_back(factor);
|
||||||
|
// }
|
||||||
|
// return true ;
|
||||||
|
//}
|
||||||
|
//
|
||||||
|
//} // \namespace gtsam
|
||||||
|
|
@ -0,0 +1,100 @@
|
||||||
|
///* ----------------------------------------------------------------------------
|
||||||
|
//
|
||||||
|
// * GTSAM Copyright 2010, Georgia Tech Research Corporation,
|
||||||
|
// * Atlanta, Georgia 30332-0415
|
||||||
|
// * All Rights Reserved
|
||||||
|
// * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
|
||||||
|
//
|
||||||
|
// * See LICENSE for the license information
|
||||||
|
//
|
||||||
|
// * -------------------------------------------------------------------------- */
|
||||||
|
//
|
||||||
|
//#pragma once
|
||||||
|
//
|
||||||
|
//#include <boost/make_shared.hpp>
|
||||||
|
//
|
||||||
|
//#include <gtsam/linear/GaussianFactorGraph.h>
|
||||||
|
//#include <gtsam/linear/IterativeSolver.h>
|
||||||
|
//#include <gtsam/linear/SubgraphPreconditioner.h>
|
||||||
|
//
|
||||||
|
//namespace gtsam {
|
||||||
|
//
|
||||||
|
///* split the gaussian factor graph Ab into Ab1 and Ab2 according to the map */
|
||||||
|
//bool split(const std::map<Index, Index> &M,
|
||||||
|
// const GaussianFactorGraph &Ab,
|
||||||
|
// GaussianFactorGraph &Ab1,
|
||||||
|
// GaussianFactorGraph &Ab2);
|
||||||
|
//
|
||||||
|
///**
|
||||||
|
// * A nonlinear system solver using subgraph preconditioning conjugate gradient
|
||||||
|
// * Concept NonLinearSolver<G,T,L> implements
|
||||||
|
// * linearize: G * T -> L
|
||||||
|
// * solve : L -> VectorValues
|
||||||
|
// */
|
||||||
|
//template<class GRAPH, class LINEAR, class VALUES>
|
||||||
|
//class SubgraphSolver : public IterativeSolver {
|
||||||
|
//
|
||||||
|
//private:
|
||||||
|
// typedef typename VALUES::Key Key;
|
||||||
|
// typedef typename GRAPH::Pose Pose;
|
||||||
|
// typedef typename GRAPH::Constraint Constraint;
|
||||||
|
//
|
||||||
|
// typedef boost::shared_ptr<const SubgraphSolver> shared_ptr ;
|
||||||
|
// typedef boost::shared_ptr<Ordering> shared_ordering ;
|
||||||
|
// typedef boost::shared_ptr<GRAPH> shared_graph ;
|
||||||
|
// typedef boost::shared_ptr<LINEAR> shared_linear ;
|
||||||
|
// typedef boost::shared_ptr<VALUES> shared_values ;
|
||||||
|
// typedef boost::shared_ptr<SubgraphPreconditioner> shared_preconditioner ;
|
||||||
|
// typedef std::map<Index,Index> mapPairIndex ;
|
||||||
|
//
|
||||||
|
// /* the ordering derived from the spanning tree */
|
||||||
|
// shared_ordering ordering_;
|
||||||
|
//
|
||||||
|
// /* the indice of two vertices in the gaussian factor graph */
|
||||||
|
// mapPairIndex pairs_;
|
||||||
|
//
|
||||||
|
// /* preconditioner */
|
||||||
|
// shared_preconditioner pc_;
|
||||||
|
//
|
||||||
|
// /* flag for direct solver - either QR or LDL */
|
||||||
|
// bool useQR_;
|
||||||
|
//
|
||||||
|
//public:
|
||||||
|
//
|
||||||
|
// SubgraphSolver(const GRAPH& G, const VALUES& theta0, const Parameters ¶meters = Parameters(), bool useQR = false):
|
||||||
|
// IterativeSolver(parameters), useQR_(useQR) { initialize(G,theta0); }
|
||||||
|
//
|
||||||
|
// SubgraphSolver(const LINEAR& GFG) {
|
||||||
|
// std::cout << "[SubgraphSolver] Unexpected usage.." << std::endl;
|
||||||
|
// throw std::runtime_error("SubgraphSolver: gaussian factor graph initialization not supported");
|
||||||
|
// }
|
||||||
|
//
|
||||||
|
// SubgraphSolver(const shared_linear& GFG, const boost::shared_ptr<VariableIndex>& structure, bool useQR = false) {
|
||||||
|
// std::cout << "[SubgraphSolver] Unexpected usage.." << std::endl;
|
||||||
|
// throw std::runtime_error("SubgraphSolver: gaussian factor graph and variable index initialization not supported");
|
||||||
|
// }
|
||||||
|
//
|
||||||
|
// SubgraphSolver(const SubgraphSolver& solver) :
|
||||||
|
// IterativeSolver(solver), ordering_(solver.ordering_), pairs_(solver.pairs_), pc_(solver.pc_), useQR_(solver.useQR_) {}
|
||||||
|
//
|
||||||
|
// SubgraphSolver(shared_ordering ordering,
|
||||||
|
// mapPairIndex pairs,
|
||||||
|
// shared_preconditioner pc,
|
||||||
|
// sharedParameters parameters = boost::make_shared<Parameters>(),
|
||||||
|
// bool useQR = true) :
|
||||||
|
// IterativeSolver(parameters), ordering_(ordering), pairs_(pairs), pc_(pc), useQR_(useQR) {}
|
||||||
|
//
|
||||||
|
// void replaceFactors(const typename LINEAR::shared_ptr &graph);
|
||||||
|
// VectorValues::shared_ptr optimize() ;
|
||||||
|
// shared_ordering ordering() const { return ordering_; }
|
||||||
|
//
|
||||||
|
//protected:
|
||||||
|
// void initialize(const GRAPH& G, const VALUES& theta0);
|
||||||
|
//
|
||||||
|
//private:
|
||||||
|
// SubgraphSolver():IterativeSolver(){}
|
||||||
|
//};
|
||||||
|
//
|
||||||
|
//} // namespace gtsam
|
||||||
|
//
|
||||||
|
//#include <gtsam/linear/SubgraphSolver-inl.h>
|
||||||
Loading…
Reference in New Issue